Long Noncoding RNA Malat1 and Neat1 Associated With Dysbiotic Microbiome and Epithelial-Mesenchymal Transition in Periodontitis.

Introduction: The regulatory mechanisms of epithelial-mesenchymal transition (EMT) involved in periodontitis pathogenesis are poorly understood. Consequently, this study aimed to investigate the association of the long noncoding (lnc) RNAs, NEAT1 and MALAT1, with EMT in periodontitis.

Methods: Gingival tissue samples (n = 57) were obtained from periodontitis patients indicated for surgical treatment and healthy control individuals. Full mouth periodontal charting was recorded for all patients together with collection of subgingival biofilm samples to determine bacterial load for key-periodontal pathogens. Histopathological analysis was used to assess inflammatory cell infiltration, and RT-qPCR analysis was performed to quantify the expression of the key EMT biomarkers of E-cadherin, β-catenin, Snail1 and vimentin, and the lncRNAs of Neat1 and Malat1.

Results: The clinical parameters and percentage of inflammatory cell infiltration were significantly higher in the periodontitis group compared with healthy controls. In periodontitis, expressions of Malat1 and E-cadherin were significantly downregulated, whereas Neat1, Snail1 and vimentin were significantly upregulated in comparison to controls. Receiver-operating characteristic (ROC) analyses demonstrated moderate-to-good diagnostic accuracy of Neat1, Malat1, Snail1, E-cadherin and vimentin (area under the curve [AUC]: 70.3%, 67.5%, 78.7%, 89.9% and 74.3%, respectively) to discriminate periodontal health from disease.

Conclusion: Probing pocket depth, bleeding scores, expression of Neat1, red complex bacteria (Porphyromonas gingivalis and Treponema denticola) and downregulation of Malat1 and E-cadherin were strongly associated with EMT. Data also highlighted an association between Neat1 and Malat1 with the induction of the EMT phenotype in periodontitis, and these lncRNAs may therefore provide novel diagnostic biomarkers.